Distributed random energy management method of ship integrated energy system

Abstract

The invention discloses a distributed random energy management method of a ship integrated energy system, and relates to the technical field of new energy and energy conservation, and the method comprises the steps: building an energy management model of the ship integrated energy system; for a distributed structure of a ship integrated energy system, variable replacement is carried out on an energy management problem of the ship integrated energy system; aiming at the influence of complex sea conditions on load requirements, simplifying the energy management model; according to the state information of different devices in the ship integrated energy system, a communication topology is constructed, a distributed stochastic optimization algorithm is adopted to solve the energy management problem of the ship integrated energy system under the complex sea condition, and optimal energy management decision parameters of the ship integrated energy system are obtained. According to the method, the energy management problem of the ship comprehensive energy system can be effectively solved, the optimal scheduling scheme is efficiently obtained under the complex sea condition, and safe navigation of the ship is guaranteed.

Description

Technical Field

[0001] The present application relates to the field of new energy and energy-saving technology, and in particular to a distributed random energy management method for a ship integrated energy system taking into account uncertain load demands. Background Art

[0002] With the booming development of the shipping industry, a large number of ships that rely on traditional energy have become the main source of pollution to the marine environment. In order to improve the marine environment and solve the energy crisis, renewable energy resources are widely used in ship integrated energy systems. In order to improve the energy utilization efficiency of ship integrated energy systems and promote the economic development of green and intelligent ships, the energy management of ship integrated energy systems has received extensive attention.

[0003] However, compared with other integrated energy systems, there are many challenges in solving the energy management problems of ship integrated energy systems due to the disturbances caused by wind, waves, currents and surges during ship navigation:

[0004] On the one hand, complex sea conditions cause disturbances to load demand and affect the stability of energy management decisions. However, the ship's propulsion equipment needs to operate safely under a stable energy supply. Under complex sea conditions, the energy demand of ships is uncertain, but there is a relative lack of in-depth research on energy management issues in ship integrated energy systems. Most past studies have focused on the diversification of energy supply equipment in ship integrated energy systems and ship navigation constraints, but have paid little attention to the impact of complex sea conditions on ship energy demand. Especially in terms of energy management decisions, existing studies often ignore the impact of uncertain loads on stable energy management decisions. These changes directly affect the stable energy supply of ship integrated energy systems to propulsion equipment.

[0005] On the other hand, processing uncertain and complex information requires a lot of computing resources, but it is very expensive to equip a sailing ship with a device with large computing resources. When processing uncertain information, existing studies have also failed to fully consider the problem of limited computing resources of the ship's integrated energy system, as well as the additional information processing process that increases computing time, affecting the real-time nature of its energy management decisions.

[0006] The existing energy management methods for integrated ship energy systems partially use centralized algorithms such as the subgradient method and the alternating direction method of multipliers (ADMM). Since the heterogeneous power generation equipment in the integrated ship energy system makes it present a distributed structure, it is necessary to explore an energy management method that adapts to its distributed operation mode. The current distributed energy management methods for integrated ship energy systems mainly solve energy management models with accurate load information, or use additional technical means to predict uncertain loads. However, equipping ships with equipment with large computing resources to process uncertain energy demand information requires high maintenance costs and requires a large amount of ship space.

[0007] Therefore, it is necessary to explore a method that can solve the energy management problem of ship integrated energy system with limited computing resources. Summary of the invention

[0008] In view of this, the present invention provides a distributed random energy management method for a ship integrated energy system considering uncertain load demand. Considering the impact of uncertain load demand on the safety of ship navigation under complex sea conditions, the present invention takes the ship integrated energy system as the research object, and establishes an energy management model of the ship integrated energy system based on the operating cost of the energy supply equipment, the supply and demand balance constraints and the ship's safe navigation constraints. Based on the theory of random optimization and distributed optimization, the present invention proposes a distributed random energy management method to improve its energy management efficiency by considering the impact of uncertain load demand on stable energy management decisions. In addition, the algorithm proposed by the present invention does not require additional information processing processes, saving computing resources of the ship integrated energy system. This method can not only effectively solve the energy management problem of the ship integrated energy system, but also efficiently obtain the optimal scheduling plan under complex sea conditions to ensure the safe navigation of the ship.

[0009] To this end, the present invention provides the following technical solutions:

[0010] The present invention discloses a distributed random energy management method for a ship integrated energy system, the steps comprising:

[0011] Establish an energy management model for the ship's integrated energy system;

[0012] According to the distributed structure of the ship's integrated energy system, the variable replacement is performed on its energy management problem; according to the influence of complex sea conditions on load demand, the energy management model is simplified;

[0013] According to the status information of different devices in the ship integrated energy system, the communication topology is constructed, and the energy management problem of the ship integrated energy system under complex sea conditions is solved by using a distributed random optimization algorithm to obtain the optimal energy management decision parameters of the ship integrated energy system;

[0014] Wherein, the distributed random energy management method comprises:

[0015] Initialization, establishing the communication topology of the ship integrated energy system, and setting the calculation cycle K;

[0016] At the kth iteration, the following local calculation is completed:

[0017]

[0018] Wherein, step size η = 0.00005;

[0019] Exchange local information:

[0020] Among them, y Ri (k) and z Ri (k) is an auxiliary variable, μ is the penalty coefficient, R is the Perron matrix of the adjacency matrix, is the penalty function gradient of the inequality constraint, is the cost function gradient, D xi is the load demand disturbance, x Ri (k) is the value of R at the kth iteration xi The estimate of x i =[P i ;H i ], R xi =[R Pi ; R Hi ];

[0021] Repeat the above steps until it iterates K times, complete the distributed optimization calculation, and obtain the optimal economic dispatch decision parameter x i ;

[0022] Based on the optimal energy management decision parameters, real-time energy task allocation is performed.

[0023] Furthermore, an energy management model for the ship's integrated energy system is established, including:

[0024] Obtain the status information of different equipment in the ship's integrated energy system; based on the operating cost parameters of different types of energy supply equipment in the ship's integrated energy system, analyze the operating cost function, take the minimum operating cost of the ship's integrated energy system as the optimization goal, follow the supply and demand balance constraints, safe power generation constraints, ship energy consumption operation constraints and speed constraints, and establish an energy management model for the ship's integrated energy system.

[0025] Furthermore, the equipment in the ship's integrated energy system includes photovoltaic panels, diesel generators, energy storage devices and cogeneration equipment.

[0026] Furthermore, the objective function of the energy management model of the ship integrated energy system is:

[0027]

[0028] Among them, C total is the total cost of the ship's integrated energy system; N1 is the number of photovoltaic panels; N2 is the number of diesel generators; N3 is the number of energy storage devices; N4 is the number of cogeneration equipment; is the cost function of the photovoltaic panel; is the cost function of the diesel generator; is the cost function of the energy storage device; is the cost function of the CHP plant; They are the state variables of the output power of photovoltaic panels, diesel generators, energy storage devices, and hotspot cogeneration devices; are the state variables of the thermal energy output of the energy storage device and the thermal energy cogeneration device;

[0029] In order to maintain the normal operation of the load, combined with the total output power of the energy supply device, the constraint conditions are:

[0030]

[0031] Among them, D P ,D H They are the total electrical and thermal energy requirements of the ship's integrated energy system;

[0032] Considering the safe operation of energy supply equipment, each device in the ship integrated energy system should operate normally under safe physical constraints. The output energy constraint of each energy supply device is:

[0033]

[0034] in, They are the upper and lower limits of the power output of photovoltaic panels, diesel generators, energy storage equipment and cogeneration equipment; They are the upper and lower limits of the heat output of the energy storage device and the cogeneration device, respectively;

[0035] The ship energy efficiency operation index EEOI constraint is:

[0036] EEOI(P DG ,H CHP )≤E max

[0037]

[0038] Among them, E max is the upper bound of the EEOI index, M C is the total load of the ship, D is the number of nautical miles, are the CO2 emissions from diesel generators and cogeneration equipment, respectively;

[0039] The relationship between carbon dioxide emissions and output power is:

[0040]

[0041] in, are the coefficients of the CO2 emission functions for diesel generators and CHP plants, respectively;

[0042] Through linearization, the carbon dioxide emission function is equivalent to:

[0043]

[0044] in, are the emission parameters after linearization;

[0045] To ensure navigation safety, the ship's speed at different stages should meet the following requirements:

[0046]

[0047] in, are the upper and lower speed limits for cruising, berthing and leaving the port respectively; the current speed of the ship is

[0048] Furthermore, the energy management model of the ship integrated energy system is as follows:

[0049]

[0050] Among them, C total (P,H) is the total energy cost, P = col[P i ],H=col[H i ],P i ,H i are the output electrical energy and thermal energy of the i-th device, respectively. For diesel generators and cogeneration equipment, E E,i =1, other devices, E E,i =0, P i min ,P i max , are the upper and lower limits of the intersection of the safe operation constraint set of the i-th device respectively;

[0051] Perform variable substitution on its energy management problem, including:

[0052] Using marginal cost to replace electricity and heat to express the total energy supply cost and various constraints, the marginal cost is expressed as follows:

[0053]

[0054] in, is the first-order partial derivative of the cost function;

[0055] By replacing variables, the energy management problem is equivalent to:

[0056]

[0057] in,

[0058] Furthermore, in view of the impact of complex sea conditions on load demand, the energy management model is simplified, including:

[0059] Based on the penalty function method, the equality constraints considering uncertain loads are processed to solve the problem of solution space changes during the iteration process, including:

[0060] Characterizing the load uncertainty during ship voyage, the energy demand is shown as follows:

[0061] D P =D P +ω p (i),D H =D H +ω H (i);

[0062] Among them, ω p (i),ω H (i) is the unknown detection noise;

[0063] The penalty function-based method reduces the impact of noise on the problem solution space. The solution to the original problem is equivalent to the solution to the following problem:

[0064]

[0065] Among them, E{·} is the expectation operator,

[0066] Based on the penalty function method, the inequality constraints in the energy management problem are relaxed and the energy management problem is expressed as:

[0067]

[0068] Among them, R xi =[R Pi ; R Hi], J Ri (R xi ) is the penalty function, which is in the form of:

[0069]

[0070] Among them, the parameter γ>0, x i =[P i ;H i ], D xi =[D Pi ;D Hi ], (u) + =max(0,u), are the penalty functions for equality constraints and inequality constraints respectively.

[0071] Advantages and positive effects of the present invention:

[0072] The present invention is an innovative technology proposed based on in-depth research and analysis of the ship integrated energy system. Based on traditional power generation equipment and renewable energy equipment, the technology establishes an energy management model for the ship integrated energy system while considering the global supply and demand balance and the constraints of ship navigation safety operation, so as to ensure the reliable and stable operation of energy supply and the safe operation of the ship. Among them, the present invention designs a distributed random energy management method, which can effectively solve the impact of uncertain load demand on stable energy supply, thereby ensuring the safe navigation of ships in complex sea conditions.

[0073] By implementing the present invention, the development of renewable energy can be effectively promoted, the dependence of ships on traditional energy can be reduced, and the development of green and intelligent ships can be further promoted. Distributed energy systems are applied in the system to achieve reliable communication between devices and complete distributed energy management decision calculations; at the same time, the distributed random energy management method can better adapt to the distributed operation mode, accommodate the disturbance in the uncertain energy demand information, and ensure the stable energy supply of the ship's integrated energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0075] Figure 1 This is a schematic diagram of the structural framework of a ship integrated energy system in an embodiment of the present invention;

[0076] Figure 2A schematic diagram of the physical structure and network structure of a ship integrated energy system in an embodiment of the present invention;

[0077] Figure 3 It is a schematic diagram of the optimal energy management decision, speed and EEOI index obtained by the centralized algorithm in an embodiment of the present invention;

[0078] Figure 4 It is a schematic diagram of the optimal energy management decision and the corresponding marginal cost under distributed random energy management in an embodiment of the present invention;

[0079] Figure 5 A schematic diagram showing the comparison between power demand detection information and actual output power in an embodiment of the present invention;

[0080] Figure 6 A schematic diagram of the total cost of a ship integrated energy system in an embodiment of the present invention;

[0081] Figure 7 Schematic diagram of the optimal energy management decision and the corresponding marginal cost under complex sea conditions in an embodiment of the present invention;

[0082] Figure 8 A schematic diagram showing the comparison between power demand detection information and actual output power under complex sea conditions in an embodiment of the present invention;

[0083] Fig. 9 Schematic diagram of energy management decision comparison of traditional distributed energy management methods under complex sea conditions in an embodiment of the present invention. DETAILED DESCRIPTION

[0084] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0085] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0086] Aiming at the energy management problem of ship integrated energy system, a distributed energy management method that can be operated under limited computing resources is provided. The present invention takes ship integrated energy system as the research object, and proposes a distributed random energy management method to accommodate the disturbance in the load in view of the disturbance of complex sea conditions on load demand. The present invention can effectively overcome the difficulty of providing stable energy supply for sailing ships under complex sea conditions, realize the improvement of energy utilization efficiency of ship integrated energy system, and ensure that the ship integrated energy system can operate stably, efficiently and safely during the voyage of the ship.

[0087] The framework of the ship integrated energy system in the present invention is as follows Figure 1 As shown in the figure, the system is based on the ship integrated energy system as the research carrier, which includes photovoltaic panels, diesel generators, cogeneration equipment, engineering power equipment, domestic electricity and ship propulsion. In order to analyze the operation mechanism and energy scheduling characteristics of the ship integrated energy system, an energy management model of the ship integrated energy system is constructed. The model considers the supply and demand balance constraints, navigation pollution index and ship safety operation constraints, with the goal of minimizing the energy supply cost. Through advanced sensor technology, the current status and energy demand information of each device in the ship integrated energy system are transmitted to the distributed energy management system, and information interaction is completed. According to the distributed random energy management method proposed in the present invention, local calculation is completed to obtain the optimal energy scheduling decision of the ship integrated energy system.

[0088] This embodiment takes a 7-node system as an example, which includes 1 photovoltaic panel (PV1), 2 diesel generators (DG1, DG2), 2 energy storage devices (SD1, SD2) and two cogeneration devices (CHP1, CHP2). Its physical topology and communication topology are as follows: Figure 2 As shown, the distributed random energy management method specifically includes the following steps:

[0089] Step 1: Obtain the status information of different equipment in the ship's integrated energy system, including photovoltaic panels, diesel generators, energy storage devices, and cogeneration equipment; Analyze the operating cost function based on the operating cost parameters of different types of energy supply equipment in the ship's integrated energy system, and analyze its energy management constraints according to the actual operating environment of the ship, including supply and demand balance constraints, safe power generation constraints, ship energy consumption operation constraints, and speed constraints.

[0090] Step 1.1: Construct the objective function of the energy management model of the ship integrated energy system as follows:

[0091]

[0092] Among them, C total is the total cost of the ship's integrated energy system; N1 is the number of photovoltaic panels; N2 is the number of diesel generators; N3 is the number of energy storage devices; N4 is the number of cogeneration equipment; is the cost function of the photovoltaic panel; is the cost function of the diesel generator; is the cost function of the energy storage device; is the cost function of the CHP plant; They are the state variables of the output power of photovoltaic panels, diesel generators, energy storage devices, and hotspot cogeneration devices; are the state variables of the thermal energy output of the energy storage device and the thermal energy cogeneration device;

[0093] Step 1.2: In order to maintain the normal operation of loads such as power propulsion systems, fuel preheating devices and other active energy devices, the constraints obtained by combining the total output power of the energy supply device are:

[0094]

[0095] Among them, D P ,D H They are the total electrical and thermal energy requirements of the ship's integrated energy system.

[0096] Considering the safe operation of energy supply equipment, each device in the ship integrated energy system should operate normally under safe physical constraints. The output energy constraint of each energy supply device is:

[0097]

[0098] in, They are the upper and lower limits of the power output of photovoltaic panels, diesel generators, energy storage equipment and cogeneration equipment; They are the upper and lower limits of the heat output of the energy storage device and the cogeneration device, respectively;

[0099] In order to reduce the pollution emissions caused by ship navigation, the Marine Environment Protection Committee of the International Maritime Organization has formulated a ship energy efficiency operation index evaluation standard, which aims to effectively restrict the carbon dioxide emissions during the navigation process of ships. The ship energy efficiency operation index (Energy Efficiency Operation Index, EEOI) is constrained as follows:

[0100] EEOI(P DG ,H CHP )≤E max

[0101]

[0102] Among them, E max is the upper bound of the EEOI index, M C is the total load of the ship, D is the number of nautical miles, are the CO2 emissions from diesel generators and cogeneration equipment, respectively.

[0103] The relationship between carbon dioxide emissions and output power is:

[0104]

[0105] in, are the coefficients of the CO2 emission functions for diesel generators and CHP equipment, respectively.

[0106] Through linearization, the carbon dioxide emission function is equivalent to:

[0107]

[0108] in, are the emission parameters after linearization.

[0109] To ensure navigation safety, the ship's speed at different stages should meet the following requirements:

[0110]

[0111] in, They are the upper and lower speed limits for cruising, berthing and leaving the port respectively.

[0112] The current speed of the ship is

[0113] Among them, the operating parameters and value ranges of the energy supply equipment cost function and constraint conditions are shown in Table 1 below.

[0114] Table 1

[0115]

[0116] At this point, step 1 of establishing the energy management model of the ship's integrated energy system is completed.

[0117] Step 2: According to the distributed structure of the ship integrated energy system, the variables of its energy management problem are replaced to reduce the computational complexity.

[0118] The energy management model of the ship's integrated energy system is as follows:

[0119]

[0120] Among them, C total (P,H) is the total energy cost, P = col[P i ],H=col[H i ],P i ,H i are the output electrical energy and thermal energy of the i-th device, respectively. For diesel generators and cogeneration equipment, E E,i =1, other devices, E E,i =0, P i min ,P i max , They are respectively the upper and lower limits of the intersection of the safe operation constraint set of the i-th device.

[0121] In order to adapt to the distributed structure of the ship integrated energy system, marginal cost is used to replace electrical energy and thermal energy to express the total energy supply cost and various constraints. The marginal cost is expressed as follows:

[0122]

[0123] in, is the first-order partial derivative of the cost function.

[0124] By replacing variables, the energy management problem is equivalent to:

[0125]

[0126] in,

[0127] At this point, the variable replacement of the energy management problem in step 2 is completed.

[0128] Step 3: In view of the impact of complex sea conditions on load demand, the uncertainty of load is characterized, and based on the penalty function method, the equality constraints considering uncertain loads are processed to solve the problem of solution space changes during the iteration process, the inequality constraints in the model are relaxed, and the energy management model of the ship integrated energy system is simplified;

[0129] Step 3.1: Characterizing the load uncertainty during ship voyage, the energy demand is as follows:

[0130] D P =D P +ω p (i),D H =D H +ω H (i);

[0131] Among them, ω p (i),ω H (i) is the unknown detection noise. In this embodiment, it is considered that the ship propulsion system is disturbed by the sea waves, resulting in a load demand with white noise disturbance.

[0132] Step 3.2: The penalty function-based method reduces the impact of noise on the problem solution space. The solution to the original problem is equivalent to the solution to the following problem:

[0133]

[0134] Among them, E{·} is the expectation operator, μ=100.

[0135] Step 3.3: Based on the penalty function method, relax the inequality constraints in the energy management problem. The energy management problem can be expressed as:

[0136]

[0137] Among them, R xi =[R Pi ; R Hi ], J Ri (R xi ) is the penalty function, which is in the form of:

[0138]

[0139] Among them, the parameter γ>0, x i =[P i ;H i ], D xi =[D Pi ;D Hi ], (u) + =max(0,u), are the penalty functions for equality constraints and inequality constraints respectively, with parameter γ = 3.

[0140] At this point, the simplification of the energy management problem in step 3 is completed.

[0141] Step 4: According to the status information of different devices in the ship's integrated energy system, construct its communication topology, design a distributed random energy management method, solve the energy management problem of the ship's integrated energy system under complex sea conditions, and obtain the optimal energy management decision of the ship's integrated energy system based on real-time energy demand information; the optimal energy management decision of the ship's integrated energy system is the decision variable output by the distributed random energy management method.

[0142] Distributed random energy management methods specifically include:

[0143] Step 4.1: Initialization, establishing the communication topology of the ship integrated energy system, and setting the calculation cycle K;

[0144] Step 4.2: At the kth iteration, complete the following local calculation:

[0145]

[0146] Among them, the step size η=0.00005.

[0147] Step 4.3: Exchange local information:

[0148]

[0149] Among them, x Ri (k) is the value of R at the kth iteration xi The estimate of x i =[P i ;H i ], R xi =[R Pi ; R Hi ];

[0150] Repeat the above steps until it iterates K times, complete the distributed optimization calculation, and obtain the optimal economic dispatch decision x i .

[0151] The present embodiment is aimed at the energy management problem of the ship leaving the port under general wave disturbance and the energy management problem under adverse weather. Figure 3 In order to solve the energy management decision, speed and EEOI of the ship departure state energy management problem under general wave disturbance using a centralized algorithm. Figure 4 The energy scheduling decision of the distributed random energy management method. The speed and range based on the optimal energy scheduling strategy meet the expected settings, and the ship can sail safely. Compared with the detected demand information, the algorithm proposed in this invention can effectively accommodate noise and obtain stable energy management decisions, such as Figure 5 As shown in Figure 2, the energy management decision obtained is the most economical, and the total cost is as follows: Figure 6 shown.

[0152] Figure 7 The energy management decision for the captain to frequently adjust the speed to cope with adverse weather. The speed adjustment task can be completed well in a short time. Compared with the detected demand information, the algorithm proposed in this invention can effectively accommodate noise and obtain stable energy management decisions, such as Figure 8 In addition, compared with the general distributed optimization algorithm, the algorithm designed by the present invention does not require filtering process, saving computing resources. Fig. 9 According to the above simulation diagram, it can be seen that the energy management method proposed in the present invention is effective.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distributed random energy management method for a ship integrated energy system, It is characterized in that The steps include: Establish an energy management model for the ship's integrated energy system; According to the distributed structure of the ship's integrated energy system, the variable replacement is performed on its energy management problem; according to the influence of complex sea conditions on load demand, the energy management model is simplified; According to the status information of different devices in the ship integrated energy system, the communication topology is constructed, and the energy management problem of the ship integrated energy system under complex sea conditions is solved by using a distributed random optimization algorithm to obtain the optimal energy management decision parameters of the ship integrated energy system; Wherein, the distributed random energy management method comprises: Initialization, establishing the communication topology of the ship integrated energy system, and setting the calculation cycle K; At the kth iteration, the following local calculation is completed: Wherein, step size η = 0.00005; Exchange local information: Among them, y Ri (k) and z Ri (k) is an auxiliary variable, μ is the penalty coefficient, R is the Perron matrix of the adjacency matrix, is the penalty function gradient of the inequality constraint, is the cost function gradient, D xi is the load demand disturbance, x Ri (k) is the value of R at the kth iteration xi The estimate of x i =[P i ;H i ], R xi =[R Pi ; R Hi ]; Repeat the above steps until it iterates K times, complete the distributed optimization calculation, and obtain the optimal economic dispatch decision parameter x i ; Based on the optimal energy management decision parameters, real-time energy task allocation is performed.

2. The distributed random energy management method of the ship integrated energy system according to claim 1, It is characterized in that Establish an energy management model for the ship's integrated energy system, including: Obtain the status information of different equipment in the ship's integrated energy system; based on the operating cost parameters of different types of energy supply equipment in the ship's integrated energy system, analyze the operating cost function, take the minimum operating cost of the ship's integrated energy system as the optimization goal, follow the supply and demand balance constraints, safe power generation constraints, ship energy consumption operation constraints and speed constraints, and establish an energy management model for the ship's integrated energy system.

3. The distributed random energy management method of the ship integrated energy system according to claim 1, It is characterized in that The equipment in the ship's integrated energy system includes photovoltaic panels, diesel generators, energy storage devices and cogeneration equipment.

4. The distributed random energy management method of the ship integrated energy system according to claim 3, It is characterized in that The objective function of the energy management model of the ship integrated energy system is: Among them, C total is the total cost of the ship's integrated energy system; N 1 is the number of photovoltaic panels; N 2 is the number of diesel generators; N 3 is the number of energy storage devices; N 4 is the number of CHP units; is the cost function of the photovoltaic panel; is the cost function of the diesel generator; is the cost function of the energy storage device; is the cost function of the CHP plant; They are the state variables of the output power of photovoltaic panels, diesel generators, energy storage devices, and hotspot cogeneration devices; are the state variables of the thermal energy output of the energy storage device and the thermal energy cogeneration device; In order to maintain the normal operation of the load, combined with the total output power of the energy supply device, the constraint conditions are: Among them, D P ,D H They are the total electrical and thermal energy requirements of the ship's integrated energy system; Considering the safe operation of energy supply equipment, each device in the ship integrated energy system should operate normally under safe physical constraints. The output energy constraint of each energy supply device is: in, They are the upper and lower limits of the power output of photovoltaic panels, diesel generators, energy storage equipment and cogeneration equipment; They are the upper and lower limits of the heat output of the energy storage device and the cogeneration device, respectively; The ship energy efficiency operation index EEOI constraint is: EEOI (P DG ,H CHP )≤E max Among them, E max is the upper bound of the EEOI index, M C is the total load of the ship, D is the number of nautical miles, are the CO2 emissions from diesel generators and cogeneration equipment, respectively; The relationship between carbon dioxide emissions and output power is: in, are the coefficients of the CO2 emission functions for diesel generators and CHP plants, respectively; Through linearization, the carbon dioxide emission function is equivalent to: in, are the emission parameters after linearization; To ensure navigation safety, the ship's speed at different stages should meet the following requirements: in, are the upper and lower speed limits for cruising, berthing and leaving the port respectively; the current speed of the ship is 5. The distributed random energy management method of the ship integrated energy system according to claim 4, It is characterized in that The energy management model of the ship integrated energy system is as follows: Among them, C total (P,H) is the total energy cost, P = col[P i ],H=col[H i ],P i ,H i are the output electrical energy and thermal energy of the i-th device, respectively. For diesel generators and cogeneration equipment, E E,i =1, other devices, are the upper and lower limits of the intersection of the safe operation constraint set of the i-th device respectively; Perform variable substitution on its energy management problem, including: Using marginal cost to replace electricity and heat to express the total energy supply cost and various constraints, the marginal cost is expressed as follows: in, is the first-order partial derivative of the cost function; By replacing variables, the energy management problem is equivalent to: in, 6. The distributed random energy management method of the ship integrated energy system according to claim 5, It is characterized in that In view of the impact of complex sea conditions on load demand, the energy management model is simplified, including: Based on the penalty function method, the equality constraints considering uncertain loads are processed and the problem of solution space changes during the iteration process is solved, including: Characterizing the load uncertainty during ship voyage, the energy demand is shown as follows: D P =D P +ω p (i),D H =D H +ω H (i); Among them, ω p (i),ω H (i) is the unknown detection noise; The penalty function-based method reduces the impact of noise on the problem solution space. The solution to the original problem is equivalent to the solution to the following problem: Among them, E{·} is the expectation operator, Based on the penalty function method, the inequality constraints in the energy management problem are relaxed and the energy management problem is expressed as: Among them, R xi =[R Pi ; R Hi ], J Ri (R xi ) is the penalty function, which is in the form of: Among them, the parameter γ>0, x i =[P i ;H i ], D xi =[D Pi ;D Hi ], (u) + =max(0,u), are the penalty functions for equality constraints and inequality constraints, respectively.

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